A No-Reference Blur Metric based on Second-Order Gradients of Image

Abstract

Estimation of blurriness value in image is an important issue in image processing applications such as image deblurring. In this paper, a no-reference blur metric with low computational cost is proposed, which is based on the difference between the second order gradients of a sharp image and the one associated with its blurred version. The experiments, in this paper, performed on four databases, including CSIQ, TID2008, IVC, and LIVE. The experimental results indicate the capability of the proposed blur metric in measuring image blurriness, also the low computational cost, comparing with other existing approaches.